Job Description

Are you seeking an environment where you can drive innovation? Do you want to be at the forefront of solving the toughest real-world supply chain problems? Do you want to play a key role in the future of Amazon's Stores business? Come and join us!
Supply Chain Optimization Technologies (SCOT) owns Amazon's global inventory planning systems. We decide what, when, where, and how much we should buy to meet Amazon's business goals and to make our customers happy. We decide how to place and move inventory within Amazon's fulfillment network. We do this for hundreds of millions of items and hundreds of product lines worth billions of dollars worldwide. Check our website if you are curious to learn more about the breadth of problems we tackle: https://www.amazon.science/tag/supply-chain-optimization-technologies

We are seeking a Sr. Manager of Applied Science with expertise in Statistical Machine Learning and/or Reinforcement Learning to drive research, development, and deployment of AI technology that empowers SCOT to build, run, and continuously improve the world's most efficient supply chain. To achieve this goal, we accelerate ML / RL software adoption through our partnerships and infrastructure. In this role, you will manage a team of scientists tasked researching the next generation of solutions to power buying, placement, and fulfillment decisions, while translating customer needs into reusable software infrastructure that accelerates adoption and deployment.

Key job responsibilities
- Lead technical innovation in reinforcement learning applications for complex supply chain environments, solving unique challenges and ensuring practical implementation in real-world deployments.
- Build and develop a high-performing team by fostering collaboration, mentoring top talent, and creating a balanced culture of technical excellence.
- Bridge technical possibilities with business requirements by providing strategic judgment, evaluating technology feasibility, and managing implementation risk.
- Drive cross-functional collaboration by interfacing with product teams, leadership, and partner organizations to translate business needs into technical solutions.

Basic Qualifications

- Ph.D. in Computer Science, Applied Mathematics, Statistics or a closely-related field.
- Hands-on experience building machine learning or optimization models in a business environment.
- Demonstrated experience managing a science team for three or more years.
- Expertise in modern Python with applications of efficient large-scale data processing in complex systems.

Preferred Qualifications

- Ability to manage and quantify improvement in multiple business areas resulting from business analytics, optimization techniques, and/or statistical modeling.
- Prior experience managing senior scientists as well as a successful record of developing junior members from academia/industry to a successful career track in a business environment.
- Significant peer-reviewed scientific contributions in premier journals and conferences.
- Familiarity with inventory planning concepts - forecasting, planning, optimization, and logistics - gained through work experience or graduate level education.
- Superior verbal and written communication and presentation skills, ability to convey rigorous mathematical concepts and considerations to non-experts.
- Proven ability to work effectively in a cross-functional team.

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $196,900/year in our lowest geographic market up to $340,300/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits This position will remain posted until filled. Applicants should apply via our internal or external career site.